CAJ | 학술논문

散斑噪声作为超声图像的主要噪声严重影响超声成像质量，滤除散斑噪声是超声图像处理过程中重要步骤。以曲波阈值去噪方法为基础，针对常用阈值函数中对较小曲波系数处理粗糙、不连续、收敛慢的缺点，通过分析实际超声图像中散斑噪声的分布，提出了具有与实际噪声分布相关特点的曲波阈值去噪方法。对比测试实验结果表明，曲波去噪方法相比其他去噪方法在不同噪声水平下均具有更加稳定优异的去噪性能，峰值性噪比提高了1~2 dB，平均结构相识度相比也有较大的提高。
산반조성작위초성도상적주요조성엄중영향초성성상질량，려제산반조성시초성도상처리과정중중요보취。이곡파역치거조방법위기출，침대상용역치함수중대교소곡파계수처리조조、불련속、수렴만적결점，통과분석실제초성도상중산반조성적분포，제출료구유여실제조성분포상관특점적곡파역치거조방법。대비측시실험결과표명，곡파거조방법상비기타거조방법재불동조성수평하균구유경가은정우이적거조성능，봉치성조비제고료1~2 dB，평균결구상식도상비야유교대적제고。
Speckle noise is the main noise which seriously affects the quality of ultrasound images. Speckle noise filtering is an important step for medical ultrasound image processing. A new curvelet denoising method based on the probability distribution of speckle is proposed, to improve the performance of the threshold function’s continuity and astringency. Comparative results show that the proposed method has stable and outstanding performance at different noise levels. The method always has better Mean Structural Similarity Index Map(MSSIM)and increases the Peak Signal to Noise Ratio (PSNR)about 1~2 dB.